potential effects of deep seawater discharge by an ocean
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Potential effects of deep seawater discharge by an OceanThermal Energy Conversion plant on the marine
microorganisms in oligotrophic watersMélanie Giraud, Véronique Garçon, Denis de la Broise, Joël Sudre, Stéphane
l’Helguen, Marie Boye
To cite this version:Mélanie Giraud, Véronique Garçon, Denis de la Broise, Joël Sudre, Stéphane l’Helguen, et al.. Po-tential effects of deep seawater discharge by an Ocean Thermal Energy Conversion plant on themarine microorganisms in oligotrophic waters. Science of the Total Environment, Elsevier, 2019, 693,pp.133491. �10.1016/j.scitotenv.2019.07.297�. �hal-02337618�
1
Potential effects of deep seawater discharge by an Ocean Thermal Energy 1
Conversion plant on the marine microorganisms in oligotrophic waters 2
3
Mélanie Giraud1,2,3, Véronique Garçon2, Denis de la Broise1, Stéphane L’Helguen1, Joël Sudre2, Marie 4
Boye1,4 5
1LEMAR (UMR 6539), IUEM, Technopôle Brest-Iroise, 29280 Plouzané - France ; 2LEGOS (UMR 5566), 31401 Toulouse cedex 9 - 6
France ; 3France Energies Marines, 29200 Brest - France ; 4Present address : Institut de Physique du Globe de Paris (UMR 7154), 75005 7
Paris, France 8
Corresponding author: M. Boye ([email protected]) 9
Science of the Total Environment 693 (2019) 133491 10 https://doi.org/10.1016/j.scitotenv.2019.07.297 11
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Abstract 13
Installation of an Ocean Thermal Energy Conversion pilot plant (OTEC) off the Caribbean coast of 14
Martinique is expected to use approximately 100 000 m3 h-1 of deep seawater for its functioning. This study 15
examined the potential effects of the cold nutrient-rich deep seawater discharge on the phytoplankton 16
community living in the surface warm oligotrophic waters before the installation of the pilot plant. Numerical 17
simulations of deep seawater upwelled by the OTEC, showed that a 3.0 °C temperature change, considered as 18
a critical threshold for temperature impact, was never reached during an annual cycle on the top 150 m of the 19
water column on two considered sections centered on the OTEC. The thermal effect should be limited, less 20
than 1 km2 on the area exhibited a temperature difference of 0.3 °C (absolute value), producing a negligible 21
thermic impact on the phytoplankton assemblage. The impact on phytoplankton of the resulting mixed deep 22
and surface seawater was evaluated by in situ microcosm experiments. Two scenarios of water mix ratio (2 % 23
and 10 % of deep water) were tested at two incubation depths (deep chlorophyll-a maximum: DCM and bottom 24
of the euphotic layer: BEL). The larger impact was obtained at DCM for the highest deep seawater addition (10 25
%), with a development of diatoms and haptophytes, whereas 2 % addition induced only a limited change of 26
the phytoplankton community (relatively higher Prochlorococcus sp. abundance, but without significant shift of 27
the assemblage). This study suggested that the OTEC plant would significantly modify the phytoplankton 28
assemblage with a shift from pico-phytoplankton toward micro-phytoplankton only in the case of a discharge 29
2
affecting the DCM and would be restricted to a local scale. Since the lower impact on the phytoplankton 30
assemblage was obtained at BEL, this depth can be recommended for the discharge of the deep seawater to 31
exploit the OTEC plant. 32
33
Keywords: marine microbial ecosystem½biogeochemistry½modeling½artificial seawater discharge½in situ 34
experiments½environmental standards 35
36
1. Introduction 37
Ocean Thermal Energy Conversion (OTEC) uses the solar energy by exploiting the temperature gradient 38
between surface and bottom seawater. In an OTEC plant, the cold deep seawater pumped close to sea bottom 39
is used to condense a working fluid (like ammonia), whereas warm surface waters, pumped close to the surface, 40
serve to evaporate it. The difference of pressure, generated by the evaporation and condensation of the fluid, 41
drives a turbine that produces mechanical energy. This energy is then converted to electrical energy in a 42
generator. Due to the need of a 20 °C difference between the cold deep and the warm surface waters for the 43
OTEC exploitation, tropical areas are well suited for the installation of OTEC plants. 44
The Martinique, a tropical island of Lesser Antilles, is ideally suited for OTEC functioning with its narrow 45
continental slope in the Caribbean part of the island, allowing an implementation of the plant close to the coast. 46
The implementation of a 10 MW OTEC pilot plant off the Caribbean coast of Martinique is expected in 2020 as 47
part of the french NEMO project (Akuo Energy, DCNS). This OTEC will pump approximately 100 000 m3.h-1 of 48
deep seawater at 1100 m depth. In order to optimize the energy efficiency, the deep seawater should be 49
rejected close to the surface. However, this large discharge could induce important disturbances on the upper 50
ocean ecosystem, and this impact should be estimated. 51
Environmental assessment of OTEC functioning was studied since the 1980’s (NOAA, 1981; 2010). The 52
deep seawater discharge was described as one of the major drivers impacting the marine environment in OTEC 53
plant. However, only a few studies specifically detailed this critical aspect (Taguchi et al., 1987; Rocheleau et al., 54
2012). The deep seawater discharge in OTEC plant generates a phenomenon similar to the one naturally 55
occurring in the ocean within upwelling systems. Equatorward winds along the coast in the eastern Atlantic and 56
Pacific linked to atmospheric high-pressure systems force Ekman transport and pumping, relocating coastal 57
3
surface waters offshore. Thereby, deep water transport towards the surface is generated close to the coast. In 58
these systems, the large amount of macronutrients and trace metals carried to the euphotic zone by the 59
enriched deep seawater supports a large development of the phytoplankton, making upwelling the most 60
productive oceanic regions (Bakun, 1990; Pauly and Christensen, 1995; Chavez and Toggweiler, 1995; Carr and 61
Kearns, 2003). By contrast, the tropical surface waters off the Caribbean coast of Martinique exhibit low 62
nutrients (nitrate and phosphate) concentrations (< 0.02 µmol.L-1) and therefore, they can be significantly 63
enriched by the deep seawater discharge. Whereas phytoplankton assemblages in upwelling systems are 64
usually dominated by large phytoplankton and particularly by diatoms (Bruland et al., 2001; Van Oostende et 65
al., 2015), the phytoplankton community in oligotrophic systems is composed of smaller organisms (Agawin et 66
al., 2000). 67
Due to these important differences in biogeochemical functioning and environmental microbiology, it is 68
thus of critical interest to investigate the potential effects of the deep seawater discharge of the planned OTEC 69
plant on the phytoplankton community off Martinique. Furthermore, it is crucial to provide a depth where the 70
deep seawater could be discharged without significant effect on the surface layer where phytoplankton is the 71
most abundant. Indeed, no environmental standards on the deep seawater discharge effects are available yet, 72
while transitional blue energies such as OTEC plants will likely expand in the near future. 73
In this study, the impact of deep seawater discharge on the thermal structure of surface waters was first 74
assessed. Modification of the surface waters stratification should indeed impact the phytoplankton community. 75
A high-resolution oceanic model was used to examine the thermal impact induced by the deep seawater 76
dispersion. Eight configurations of discharge depth were tested, corresponding to the deep chlorophyll-a 77
maximum (DCM), the bottom of the euphotic layer (BEL) and five depths below the BEL. Temperature 78
differences between numerical simulations without and with the deep seawater discharge were compared on 79
the upper 150 m of a vertical section. 80
The distribution of the ambient phytoplankton community and the biogeochemical properties of the deep 81
and surface seawater mixture that could impact the phytoplankton community were then described. 82
Phytoplankton distribution and assemblage were detailed in order to assess short time and small scales 83
variabilities of phytoplankton assemblage and primary production in the study site. 84
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Finally, in order to simulate the OTEC deep seawater input, enrichment experiments were conducted on 85
the future site of the pilot plant. Enrichment experiments are commonly used in oceanography to assess the 86
effects on phytoplankton community and primary production. For example, large iron (Fe) enrichment 87
experiments were conducted from 1993 to 2005 to estimate the potential of Fe limitation on ocean primary 88
production (De Baar et al., 2005; Boyd et al., 2007). Several experiments also showed that macro- and micro-89
nutrients enrichments induce changes in the phytoplankton community in upwelling regions (Hutchins et al., 90
2002) as well as in oligotrophic regions (Kress et al., 2005). Enrichment experiments were usually conducted with 91
mesocosms immerged close to the surface (Escaravage et al., 1996; Duarte et al., 2000) or in laboratory under 92
artificial light and temperature using phytoplankton model species (Brzezinski, 1985). A laboratory experiment 93
intended to evaluate the effects of an OTEC seawater discharge in Hawaiian waters on the natural 94
phytoplankton community was previously conducted (Taguchi et al., 1987) under such artificial conditions, and 95
thus, it could not totally reproduce what occurred in the natural environment. Other deep seawater discharge 96
experiments were realized in situ (Aure et al., 2007; Handå et al., 2014). For example, the use of a moored 97
platform to upwell deep seawater and discharge it close to the surface has shown an increase in primary 98
production in a western Norwegian fjord where the euphotic zone is nutrient-depleted during summer (Aure et 99
al., 2007), as it would be expected with the OTEC discharge in oligotrophic waters. Whereas such a pumping 100
system is well adapted for pumping seawater at 30 m depth for example, it cannot be applied for OTEC 101
experiments where deep seawater must be collected far deeper (1100 m depth) and also discharged more 102
deeply in the water column to reduce the potential effects on the phytoplankton community. These conditions 103
can be obtained by the use of in situ microcosms, in which light and temperature are the same as in the natural 104
surrounding waters, avoiding additional bias, and several conditions (enrichment, incubation depth) can be 105
simulated. Therefore, we used the unique device of immerged microcosms we developed (Giraud et al., 2016) 106
for assessing the effects of deep seawater discharge on the phytoplankton community. Two incubation depths 107
(DCM and BEL) with two ratios of enriched seawater (mixtures of surface water with 2 % and 10 % of deep 108
seawater) were tested. 109
These experiments allowed the evaluation of critical mixing rate and discharging depth where effect was 110
maximal. 111
2. Materials and methods 112
5
2.1. Modelling the thermal effect 113
The hydrodynamic numerical model ROMS-Regional Ocean Model System (Shchepetkin and McWilliams, 114
2005; 2009) was used to describe the resulting thermal effect due to OTEC functioning. The model was run in a 115
2-ways AGRIF configuration allowing to define a parent and child domains around the Martinique Island which 116
are run simultaneously, transferring automatically open boundary conditions. The parent grid ranges from 63° 117
W to 59° W and 13° N to 15.9° N with a resolution of 1/60° (around 1.8 km) while the child domain narrows the 118
parent one and was from 61.74° W to 60.41° W and 14.21° N to 15.11° N with a resolution down to 1/180° 119
(around 600 m). The bottom topography and coastline are interpolated from the GINA database (1/120°, 120
www.gina.alaska.edu/data/gtopo-dem-bathymetry) (Fig. 1). The model is forced by the monthly Climate 121
Forecast System Reanalysis (NCEP-CFSR) for wind stress, heat and freshwater fluxes. For the open boundary 122
conditions and initial conditions of the parent domain, a monthly climatology computed from the Simple Ocean 123
Data Assimilation (SODA) reanalysis (Carton and Giese, 2008) was used for the dynamical variables 124
(temperature, salinity and velocity fields). The configurations were run without and with a deep seawater 125
discharge mimicking the OTEC functioning (Giraud, 2016). Eight cases of horizontal discharge settings were 126
simulated at different depths: i) the DCM (45 m), ii) the BEL (80 m), that were estimated on June 12th 2014, and 127
3) six depths below the euphotic zone (110 m, 140 m, 170 m, 250 m, 350 m and 500 m). In the OTEC plant, 128
deep water will be pumped at 1100 m where temperature is around 5 °C and salinity 35. Circulation of this 129
water through the plant system will warm it up until 8 °C prior to its release in the upper ocean. We thus 130
applied at the location of the OTEC plant (61°13’0’’ W, 14°35’48’’ N), a cold-water discharge (temperature 8 °C, 131
salinity 35) at a flow rate of 28 m3 s-1 and with a northward orientation. The thermal impact of the cold-water 132
source was assessed documenting the differences between simulations without and with the modelled OTEC 133
plant functioning (Giraud, 2016). 134
2.2. Field observations and in situ experiments 135
2.2.1. Sampling and analytical methods 136
Temperature, salinity, and fluorescence profiles were performed on 12th, 13th, 18th and 19th of June 2014 137
using Seabird SBE19+ probe with in situ Fluorimeter Chelsea AQUAtracka III. 138
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Seawater was collected on 12th and 18th of June 2014 in the water column in ultra-clean conditions (Giraud 139
et al., 2016) to measure in situ parameters and to prepare the microcosms. Seawater and microcosms were 140
sampled similarly in a land laboratory a few hours after collection. 141
Nitrate (NO3-), nitrite (NO2-), phosphate (PO43-) and silicate (Si(OH)4) concentrations were determined in 142
filtered waters (<0.6 μm; PC membrane) stored at -20 °C until analysis using a Bran + Luebbe AAIII auto-143
analyzer (Aminot and Kérouel, 2007). 144
Filtered samples (0.2 μm; 300AC-Sartobran™ capsules) for dissolved trace metals determination were 145
collected under pure-N2 pressure (0.7 atm) in acid cleaned low density polyethylene bottles, acidified with 146
ultrapure HCl (pH < 2) and stored in two plastic bags in dark at ambient temperature. Concentrations of 147
dissolved trace metals (cadmium: Cd; lead: Pb; iron: Fe; zinc: Zn; manganese: Mn; cobalt: Co; nickel: Ni; and 148
copper: Cu) were determined in UV-digested samples by ID-ICP-MS (Milne et al., 2010) after preconcentration 149
on a WAKO resin (Kagaya et al., 2009) using an Element XR ICP-MS. Blanks, limits of detection, accuracy and 150
precision (assessed using reference samples) of the ID-ICP-MS method are reported in Table 1. The values 151
determined by ID-ICP-MS were in excellent agreement with the consensus values, apart for Cd that yielded 152
higher concentration in S-SAFE reference sample than the consensus value (Table 1). 153
The pH was determined using a pH ultra-electrode (pHC28) mounted on a HQ40d multi pH-meter (HACH) 154
with an accuracy of ± 0.002 pH unit in samples preserved with saturated HgCl2 in glass bottles hermetically 155
closed with Apiezon grease, sealed with Parafilm® and stored in the dark at ambient temperature. 156
Three complementary methods were used to analyze the phytoplankton community. Pigment signatures 157
were measured by HPLC (using an Agilent Technologies 1100-series) on polysulfone filters (0.22 μm pore-size) 158
frozen at -20 °C and stored in liquid nitrogen, after internal standard addition (vitamin E acetate) and extraction 159
in a 100 % methanol solution (Hooker et al., 2012). Fifty pigments were identified and associated to 160
phytoplankton groups (Uitz et al., 2010). Identification and enumeration of pico-phytoplankton were realized by 161
flow-cytometry using a BD-FACSVerse™ (Marie et al.,1999) in samples preserved in cryotube with addition of 162
0.25 % glutaraldehyde frozen at -20 °C and stored in liquid nitrogen. Four groups of pico-phytoplankton were 163
identified: Prochlorococcus, picoeukaryotes (< 10 μm), and 2 groups of Synechococcus discriminated, 164
respectively, by their low and high phycourobilin (PUB) to phycoerythrobilin (PEB) ratios. Taxonomic 165
identification and enumeration of micro-phytoplankton (20-200 µm) and a part of nano-phytoplankton (2-20 µm) 166
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(Dussart, 1966) were carried out using an inverted microscope (Wild M40) in samples preserved with neutral 167
lugol solution. Utermöhl settling chambers (Hasle, 1988) were used for micro-phytoplankton analyses, and a 168
smaller sedimentation chamber (2.97 mL) for the analyses of nano-phytoplankton. When possible, 169
phytoplankton was identified to the lowest possible taxonomic level (species, genus or group) using the 170
classical manual for marine phytoplankton identification (Thomas, 1996) and the World Register of Marine 171
Species database (WoRMS Editorial Board, 2019). Biovolume of each species was also estimated from these 172
microscope analyses (Hillebrand et al., 1999). 173
2.2.2. In situ microcosm experiments 174
The potential impact of deep seawater discharge on the phytoplankton community was simulated by in 175
situ microcosm incubations of various deep and surface seawater mixing (Giraud et al., 2016). The experiments 176
were conducted from 12th (D0) to 19th (D7) of June 2014. The deep and surface seawaters were collected at the 177
site of the future OTEC pilot plant (61°11’52’’ W-14°37’57’’ N; Fig. 1). Microcosms bottles were incubated on 178
two stainless steel structures set at the depths of deep chlorophyll-a maximum (DCM) and at the bottom of the 179
euphotic layer (BEL) on a mooring chain located, for practical reasons, closer to the coast (61°10’9’’ W-14°39’8’’ 180
N, seafloor at 220 m depth) during 6 days (Giraud et al., 2016). This incubation time was chosen to represent the 181
short-term phytoplankton response time to a mixing of deep water with surface waters. 182
This duration is shorter or equal than the residence time of the enriched water mass, which is less than one 183
month. 184
Seawater was collected at D0 at the depths of DCM (45 m depth) and BEL (80 m depth) identified on the 185
future OTEC site from the fluorescence profile, and close to the bottom (1100 m depth corresponding to the 186
pumping depth of the future OTEC plant) in ultra-clean conditions. Deep seawater was mixed in three 187
proportions (0 % as a control hereafter referred to as "Control", 2 % as a low input called "2 % of deep 188
seawater", and 10 % as a large input called "10 % of deep seawater") with DCM and BEL waters. Each resulting 189
mixture was distributed in 2.3 L polycarbonate bottles filled up to overflow level, of which four replicates per 190
mixing condition per depth were immersed at their respective sampling-depth for 6 days; duplicates per mixing 191
condition per depth were kept in dark at 25 °C for a few hours until sampling for later characterization of 192
phytoplankton assemblage and biogeochemical properties at D0 (called "Surrounding waters D0"); and 193
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duplicates per mixing condition per depth were used to estimate carbon and NO3- uptakes at D0 (called 194
"Surrounding waters D0") as described below. 195
Same sampling and mixtures were realized at day 6 (D6, June 18th) just to evaluate the temporal evolution in 196
the natural environment, resting on duplicate bottles per mixing condition per depth for phytoplankton and 197
biogeochemical characterizations at D6 (called "Surrounding waters D6") and using other duplicates to estimate 198
carbon and NO3-uptakes at D6 (called "Surrounding waters D6"). 199
After the 6 days incubation, all the incubated microcosm bottles on the mooring (called "Microcosm D6") 200
were brought on board. A quarter of each four replicates per condition was put in a new 2.3 L clean bottle and 201
used to estimate carbon and NO3- uptakes after 6 days of incubation (called "Microcosm D6"). The remaining 202
microcosm contents were kept for sampling and analysis. 203
2.2.3. Carbon and nitrate uptakes 204
Carbon (primary production) and NO3- uptake rates were estimated in the same sample using the dual 205
13C/15N isotopic label technique (Slawyk et al., 1977). Immediately after sampling, 13C tracer (NaH13CO3, 99 206
atom%, Eurisotop, 0.25 mmol13C.mL-1) and 15N tracer (Na15NO3, 99 atom%, Eurisotop, 1 µmol15N.mL-1) were 207
added to seawater mixtures at 10-3:1 v/v ratio. The initial enrichment was 10 atom% excess of 13C for the 208
bicarbonate pool and 16-95 atom% excess of 15N for the NO3- pool depending on the ambient NO3- 209
concentration. The 13C/15N amended bottles were incubated for 24 h on the mooring line at the DCM and BEL 210
depths, after which 1 L samples were filtered onto pre-combusted (450 °C, 4 h) glass fiber filters (Whatman). 211
Filters were stored at -20 °C and oven dried (60 °C, 24 h) prior to analysis. Concentrations of carbon (POC), 212
nitrogen (PON) as well as 13C and 15N enrichments in particulate matter were measured with a mass 213
spectrometer (Delta plus, ThermoFisher Scientific) coupled to a C/N analyzer (Flash EA, ThermoFisher 214
Scientific). Standard deviations were 0.009 µM and 0.004 µM for POC and PON, and 0.0002 atom% and 0.0001 215
atom% for 13C- and 15N-enrichments, respectively. 216
The absolute uptake rates (r, in µmol.L-1.h-1) were calculated for nitrogen (Dugdale and Wilkerson, 1986) 217
and carbon (Fernández et al., 2005) using the particulate organic concentrations measured after 24 h of 218
incubation. These rates were converted into biomass specific uptake rates (VC or VNO3-, in µmol.(µg Chl a)-1.h-1) 219
by dividing r by the total chlorophyll a concentration (TChl a defined as the sum of chlorophyll a and divinyl 220
chlorophyll a) measured at the end of the incubations. The addition of 15N tracer would cause a substantial 221
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increase in dissolved inorganic nitrogen concentrations especially in the surface waters and, in turn, an 222
overestimation of uptake rates (Dugdale and Wilkerson, 1986; Harrison et al., 1996). The NO3- uptake rates 223
were corrected for this perturbation (Dugdale and Wilkerson, 1986) using a half-saturation constant of 0.05 224
µmol.L-1 characteristic for nitrogen-poor oceanic waters (Harrison et al., 1996) and the measured NO3- 225
concentration. Overestimation was low (< 5 %) in samples with an addition of deep seawater but it was of about 226
50 % in samples without deep seawater addition. The uptake rates measured in these samples represented 227
therefore estimations rather than actual values. 228
2.2.4. Statistical analyses 229
Kruskal-Wallis test was applied on the set of pigments concentrations, pico-phytoplankton abundances 230
and macronutrients concentrations. If significant differences (p < 0.05) were found, Mann-Whitney test was run 231
to identify the samples significantly different. Statistical analyses were performed using Statgraphics Centurion 232
XVI software. 233
3. Results 234
3.1. Impact of the deep seawater discharge on the thermal and density structure in surface 235
The representation of the thermocline and halocline depths, key proxies for oceanic mixing and for 236
estimating the thermal impact of the OTEC discharge, is well mimicked over the 2 months (June and 237
November) of the mesoscosm experiments (Giraud, 2016). In order to assess the deep seawater discharge 238
impact on the thermal structure of the upper 150 m of the water column, the dispersion of temperature 239
differences (ΔT in °C) obtained without and with the deep seawater discharge in the model outputs was 240
examined on two vertical sections. A section of 124 km for the large domain (corresponding to the child 241
domain) and another section of 10 km for the near-OTEC domain (defined from 61.24° W to 61.17° W and 242
14.60° N to 14.67° N) were defined, both centered on the OTEC site and parallel to the coast (Fig. 1). 243
Presently, there are no environmental standards defining threshold levels for temperature difference that 244
will be induced by an OTEC deep seawater discharge. So, the study relied on the World Bank Group 245
prescriptions for liquefied natural gas facilities which set at 3 °C the temperature difference limit at the edges of 246
the zone where initial mixing and dilution take place (IFC, 2007). We thus considered for each discharge depth 247
the cooling and warming outputs from the model, which exhibit a |ΔT| ≥ 3 °C. Areas (in % of the considered 248
domain) impacted by these cooling and warming effects were added (absolute values) in order to compare the 249
10
potential impact of each discharge depth configuration. None of the discharge depth configurations could 250
produce a modification of the thermal structure of the top 150 m of the water column, higher than or equal to 251
the considered temperature threshold (|ΔT| ≥ 3 °C), for both domain sections. 252
Then, a lower temperature difference of 0.3 °C (absolute value) was considered. This temperature 253
difference represented a low threshold as compared to the World Bank Group prescriptions (IFC, 2007) that 254
instead represent a high threshold. The areas exhibiting a |ΔT| ≥ 0.3 °C in the top 150 m (Table 2) were 255
extremely small (< 1 km2) and were not significantly different in both sections and at the different discharge 256
depths, on an annual average and in June (our experimental period). 257
We also investigated the OTEC impact on density. The density of water being discharged at 45 m, depth 258
of the deep chlorophyll maximum (DCM), is 27.48 (8°C and salinity of 35). The density of water at 45 m is 259
around 23.72 (temperature of 28°C and salinity of 36.5) so the nominal density gradient is of 3.76. If one 260
considers a modification of the density structure of the top 150 m of the water column of |Dr| ≥ 0.1, there is no 261
impact when the discharge occurs at the depth of the DCM. If one considers a lower density difference of 0.05 262
(absolute value), the area exhibiting a |Dr| ≥ 0.05 in the top 150 m is extremely small (< 1.5 km2) in both sections 263
at the depth of the chlorophyll maximum. As far as we know, there are no environmental standards defining 264
threshold levels for density difference that will be induced by an OTEC deep seawater discharge. This 265
represents less than 1.5 % of the nominal density gradient so as for the thermal impact, the impact is estimated 266
to be minor. 267
3.2. Biogeochemical properties and phytoplankton community 268
3.2.1. Expected biogeochemical properties of the resulting mixed waters 269
The pH was very similar at the DCM and BEL at the OTEC site on D6 (8.24 and 8.25, respectively), whereas 270
deep seawater-pH showed lower value (7.81). The addition of 2 % and 10 % deep seawater to surface waters 271
could thus induce a pH-decrease of respectively, 0.01 and 0.07 unit. Hence, the effect on pH could be rather 272
limited compared to the 0.1 pH decrease (from 8.2 to 8.1) between the pre-industrial time and the 1990’s (Orr 273
et al., 2005). 274
NO3- and PO43- concentrations (Table 3) were below the detection limit (< 0.02 µM) at the DCM (55 m) and 275
BEL (80 m) at the OTEC site on observational D4 (June 16th 2014), whereas Si(OH)4 concentrations were above 276
detection limit (> 0.08 µM), particularly at the DCM (2.4 µM). NO2- concentrations showed the highest values at 277
11
the BEL whereas they were negligible at the DCM (<0.02 µM). In deep seawater, as commonly observed, NO3-, 278
PO43- and Si(OH)4 concentrations were largely higher compared to the surface (Table 3). The 2 % and 10 % deep 279
water additions represented a large input for NO3- in surface waters (from <0.02 µM to 0.54 and 2.71 µM, 280
respectively; Table 3). If the 10 % ratio also induced a large input of PO43- (from <0.02 to 0.19 µM), the input of 281
2 % deep water was more limited (0.04 µM). The effect of 2 % or 10 % deep seawater addition was more 282
limited for Si(OH)4 relatively to NO3- and PO43- input, yet it accounted for 50-63 % increase for 10 % deep 283
seawater addition (Table 3). Finally, because deep and DCM waters were NO2- depleted, the deep seawater 284
input did not modify the NO2- concentration at the DCM. At the BEL, NO2- concentration was higher and the 10 285
% addition slightly diluted NO2- at this depth. 286
Mn showed maximum concentrations in the surface layer on D4 at the OTEC site (Table 4) decreasing with 287
depth as observed close to the Lesser Antilles in the Atlantic Ocean (Mawji et al., 2015), but the measured 288
surface concentrations were particularly high, especially at the DCM. Fe that commonly dispatches hybrid 289
distribution combining a nutrient-type profile in surface waters and a scavenged-type distribution in deep 290
waters (Bruland, 2003) also exhibited high surface values, particularly at the DCM (Table 4). Cd, Zn, Co, Ni, and 291
Cu dispatched nutrient-type profiles, whereas Pb exhibited scavenged-type profile (Nozaki, 1997; Gruber, 292
2008), but like for dissolved Fe and Mn, their concentrations in the upper waters were particularly high (Table 293
4). For all trace metals at both depths, the 2 % deep seawater addition will not induce significant changes in 294
their surface concentrations (Table 4). The 10 % deep seawater addition could increase Cd, Ni and Zn 295
concentrations in surface waters (Table 4), whereas it would not constitute an input of Pb, Cu, Co, and Fe, and it 296
can even dilute Mn (Table 4). 297
The surface waters can thus be enriched in macronutrients (NO3-, PO43-) when submitted to a deep 298
seawater discharge (particularly with 10 % deep seawater addition) in proportion depending on the depth. The 299
same scheme can be applied in some of the dissolved trace metals (Cd, Ni, Zn) when a large ratio of deep 300
seawater (10 %) is discharged. 301
3.2.2. Phytoplankton community in the natural environment 302
A set of seven accessory pigments identified as biomarkers of specific taxa (Uitz et al., 2010; Table 5) were 303
analyzed at OTEC station at D0, D4 and D6 in surrounding surface waters (Fig. 2), as well as population 304
abundance and their biovolume using light microscopy (Fig. 3). 305
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TChl a, a proxy of the phytoplankton biomass, was higher at DCM than at BEL, as usually observed, by 306
about two-folds. The fucoxanthin (biomarker of diatoms) concentrations were similar at the DCM and BEL on D0 307
(Fig. 2), like the total abundance of diatoms (Fig. 3). Fucoxanthin concentration increased by D4 and then by D6 308
at the DCM, corresponding to increases of cumulated diatoms biovolume on D4 (Fig. 3) and of diatoms 309
abundance on D6 (Fig. 3). Peridinin, a biomarker of dinoflagellates, was detected at the DCM unlike at the BEL, 310
with relatively high abundance and biovolume of dinoflagellates (Fig. 3). The 19’-hexanoyloxyfucoxanthin 311
(biomarker of haptophytes) concentration (Fig. 2) and the prymmnesiophytes (haptophyte) abundance and 312
biovolume (Fig. 3) showed higher values at the DCM than at the BEL only at D4. 313
At the DCM, dinoflagellates largely dominated the nano- and micro-phytoplankton assemblage with the 314
largest abundance and biovolume. Whereas prymnesiophytes showed the second highest abundance, its 315
biovolume was very low, on the contrary to diatoms that dispatched lower abundance but higher biovolume 316
(Fig. 3). At the BEL, dinoflagellates, prymnesiophytes and diatoms showed similar abundance, dinoflagellates 317
and the diatoms occupied the major part of the total biovolume. Three groups of dinoflagellates were observed 318
by light microscopy but they could not be identified at species level. However, their small size and the lack of 319
colored starch (using lugol) in the cytoplasm suggested they were mixotrophic or heterotrophic population. 320
Furthermore, the low concentrations of peridinin in samples supported this assumption. 321
At both depths, light microscopy analyses suggested that the large cyanobacteria, mainly 322
Trichodesmium sp., were low in abundance and biovolume. Flow cytometry identification and count 323
indicated that the small cyanobacteria Prochlorococcus dominated the pico-phytoplankton assemblage, 324
but they showed a significant decrease from D0 to D6 (Fig. 4). A significant portion of Synechococcus 325
was also observed while picoeukaryotes were poorly represented. Both Prochlorococcus and 326
Synechococcus showed higher abundance at the DCM than at the BEL (by 65 % and 86 %, 327
respectively), in line with the pigment analyses of zeaxanthin (biomarker of cyanobacteria) and total 328
chlorophyll b concentrations (prochlorophytes). 329
3.2.3. Primary production and nitrate uptake in the natural environment 330
The phytoplankton distribution and assemblage can partly drive the intensity of primary production, so the 331
specific uptake rate of carbon (VC; Fig. 5) and NO3- (VNO3-) were estimated at D0 and D6. 332
13
VC in surrounding surface waters was relatively low at D0 (Fig. 5) indicating low primary production in these 333
poor-nutrients waters. Yet, VC was approximately three-times higher at the DCM (0.058 µmol C.(µg Chl a)-1.h-1) 334
than at the BEL (0.017 µmol C.(µg Chl a)-1.h-1) at D0, but drastically decreasing on D6 at the DCM (to ~0.014 335
µmol C.(µg Chl a)-1.h-1). VNO3- were also very low at D0 (0.014 µmol N.(µg Chl a)-1.h-1 at DCM, 0.017 µmol N.(µg 336
Chl a)-1.h-1 at BEL) and drastically decreased at D6, below the detection limit (data not shown). 337
3.3. Impacts on the phytoplankton community of the deep seawater discharge 338
3.3.1. Changes in the phytoplankton assemblage 339
At the DCM, TChl a was similar in all treatments (p < 0.05) after 6 days of incubation in microcosms (Fig. 340
6). Only fucoxanthin and 19’-butanoyloxyfucoxanthin showed significant (p < 0.05) higher concentrations in 10 341
% enrichments as compared to controls, indicating higher abundance and/or biovolume of diatoms and 342
haptophytes. The other diagnostic pigments did not show any significant difference between enriched 343
microcosms and controls. Picoeukaryotes and Synechococcus abundances did not show significant variations 344
between the treatments (Fig. 7a). Reversely, Prochlorococcus population showed higher (p < 0.05) abundance 345
both in 2 % and 10 % enriched microcosms as compared to controls (Fig. 7a). 346
At the BEL, after the 6 days incubation period, pigments concentrations were below the detection limit 347
indicating very low abundance of phytoplankton. Pico-phytoplankton did not show significant variations 348
between the treatments and the controls (Fig. 7b). Pico-phytoplankton were clearly much less abundant at the 349
BEL (< 1000 cells.mL-1) than at DCM (Fig. 7b), 20-times even lower than that observed in surrounding waters at 350
this depth on D6. For comparison, total abundance at the DCM was ~5-times lower in incubated microcosms on 351
D6 compared to surrounding surface waters. 352
3.3.2. Changes in the primary production and nitrate uptake 353
Deep water inputs (2 % and 10 %) to surrounding waters collected at the DCM on D0 led to an increase of 354
VC within 24 h compared to the controls (by 42 % and 49 %, respectively; Fig. 5); but they had no effect on D6 355
despite very low value in natural waters at this depth (0.014 µmol N.(µg Chl a)-1.h-1). The 6 days incubated 356
microcosms showed very low VC in all treatments (Fig.5). At the BEL, VC were quite similar on D0 and D6 and 357
after 6 days of incubation. Vc increased by 57% with 10% addition of deep water on Do and was approximately 358
two times higher than the control with the two enrichments on D6 (Fig. 5). VNO3- measured in microcosms after a 359
6-days in situ incubation were below the detection limit (data not shown). 360
14
4. Discussion 361
4.1. Natural variabilities in the oligotrophic area 362
4.1.1. Biogeochemistry and phytoplankton community structure 363
The very low PO43- and NO3- concentrations recorded in the oligotrophic surrounding surface waters were 364
likely favorable to the development of small phytoplankton, especially to the cyanobacteria as shown with the 365
significant occurrence of Prochlorococcus in these waters, which are typical of poor nutrient waters (Partensky et 366
al., 1999). In line with the very low VNO3- measured here, it has been shown that VNO3- by Prochlorococcus 367
represents indeed only 5-10 % of its nitrogen uptake whereas reduced nitrogen substrates (NO2-, ammonium, 368
and urea) uptake accounts for more than 90-95 % (Casey et al., 2007). By contrast, the development of larger 369
phytoplankton taxa (particularly diatoms), which have higher NO3- and PO43-requirements for their growth, were 370
probably limited by these elements. Actually, NO3- and PO43- concentrations in surrounding waters at the DCM 371
were both lower than the detection limit (< 0.02 µM at D4) which is much lower than the average values of half-372
saturation constants for diatoms (1.6 ± 1.9 µM for NO3- and 0.24 ± 0.29 µM for PO43-; Sarthou et al., 2005). For 373
Si(OH)4, surrounding surface concentrations at DCM (2.39 µM) were in the range of diatoms half-saturation 374
constants (3.9 ± 5.0 µM; Sarthou et al., 2005), hence the diatoms development was probably not limited by 375
Si(OH)4. Furthermore, diatoms showed low abundance in spite of relatively high Si(OH)4 and dissolved trace 376
metals (in particular Fe) concentrations in surface waters. The potential of Fe limitation on phytoplankton 377
community has been reported previously in upwelling systems, with an apparent half-saturation constant for 378
diatoms growth of 0.26 nM Fe in the Peru Upwelling system (Hutchins et al., 2002). This constant is far lower 379
than the concentration of Fe measured in surrounding waters at DCM (1.08 ± 0.03 µM at D4), suggesting that 380
diatoms were probably not limited by Fe. This further supports growth limitation of diatoms by NO3- and/or 381
PO43-. 382
Advection of waters from Amazon and Orinoco rivers can explain the relatively high Si(OH)4 observed in 383
the Caribbean Sea. However, little information is available on the input of trace metals by these waters into the 384
Caribbean Sea. Amazon river can be a source of dissolved Fe, Cu, Ni, Pb and Co for the western-subtropical 385
North Atlantic (Tovar-Sanchez and Sañudo-Wilhelmy, 2011), but this input can decrease rapidly away from its 386
source like it has been shown for Co in the Western Atlantic (Dulaquais et al., 2014). Those inputs into the 387
Caribbean Sea will have to be further examined, especially for Fe, Cd, Ni, Zn, Mn whose relatively high 388
15
concentrations were detected in the Si(OH)4-enriched surface waters of this study. Additionally, other inputs of 389
trace metals such as atmospheric deposition can also increase surface concentrations, and those inputs can be 390
substantial (Shelley et al., 2012). 391
4.1.2. Primary production 392
Primary production rates measured in the oligotrophic surrounding waters were in the lower range of 393
values reported for oligotrophic waters (Laws et al., 2016; Teira et al., 2005). Despite low VC on D0 and D6 at 394
the DCM, primary production still indicated much higher value on D0 compared to D6 that was associated with 395
higher TChl a (Fig. 2a). The decrease of divinyl-chlorophyll a concentration, a biomarker of Prochlorococcus 396
(Goericke and Repeta, 1992), over the 6 days of observation can account for the decrease of TChl a, whereas 397
chlorophyll a concentrations did not vary significantly during this period. The Prochlorococcus abundance was 398
also lower by two-times on D6 compared to D0 (Fig. 4a). On the contrary, fucoxanthin (diatoms) increased by 399
four-times over the 6 days (Fig. 2a), as well as the diatoms abundance (by three-times; Fig. 3a). In turn, the 400
increase in diatoms abundance was not associated with an increase in primary production. Instead, the 401
observed decrease in primary production can be due to the decrease in Prochlorococcus abundance. In tropical 402
and subtropical waters, pico-phytoplankton can indeed contribute to more than 80 % of the primary production 403
(Platt et al., 1983; Goericke and Welschmeyer, 1993). The development of diatoms population likely did not 404
compensate the large decrease in Prochlorococcus abundance (from 141,000 to 63,000 cells.mL-1). 405
4.2. Impact of deep seawater discharge 406
4.2.1. Temperature effects 407
The numerical simulation showed that the area impacted in the top-150 m by a temperature difference 408
larger than or equal to 0.3 °C (absolute value) was lower than 1 km2 (~2-3 % of the considered domain) and was 409
insensitive to the injection depth or to the size of the tested domain (Table 2). The impact of a 0.3 °C 410
temperature variation on the growth of diatoms, notably on Pseudonitzschia pseudodelicatissima species that 411
were observed in our study area, is limited to a change in the growth rate of 0.03 d-1 (Lundholm et al., 1997). 412
For Synechococcus, a 0.3 °C variation of the temperature would also have a limited impact on the growth, with 413
a variation of only 0.02 d-1 (Boyd et al., 2013), like for Emiliania huxleyi (coccolithophyceae) for which the 414
induced variation of maximum growth rate will be lower than 0.01 d-1 (Fielding, 2013). The thermal effect on the 415
phytoplankton assemblage could thus be considered negligible. 416
16
4.2.2. Impact on the phytoplankton community 417
Microcosms enrichment of DCM waters with 10 % of deep seawater led after 6 days to a significant 418
increase (p < 0.05) of fucoxanthin (diatoms) and 19'-butanoyloxyfucoxanthin (haptophytes) by 71 % and 77 %, 419
respectively, as compared to the controls. If the 2 % enrichment also showed similar trends, the differences of 420
diagnostic pigments concentrations were not significant. NO3- and PO43- concentrations induced by 10 % deep-421
water input on D0 (2.57 ± 0.13 µM and 0.14 ± 0.2 µM, respectively; Giraud et al., 2016) were close to NO3- and 422
PO43- half-saturation constants of diatoms (1.6 ± 1.9 µM and 0.24 ± 0.29 µM, respectively; Sarthou et al., 2005). 423
The 10 % enrichment could thus support a development of diatoms. On the contrary, NO3- and PO43- 424
enrichments induced by 2 % addition of deep-water were too low (0.57 ± 0.02 µM and 0.04 ± 0.00 µM, 425
respectively; Giraud et al., 2016) compared to these half-saturation constants to support the diatoms 426
development. Therefore, the diagnostic pigments suggested a significant response proportionally to the 427
amount of added deep seawater. 428
Prochlorococcus were also more abundant (p < 0.05) in 2 % and 10 % treatments as compared to the 429
controls. This lack of further Prochlorococcus population increase in 10 % treatments could be attributed to a 430
higher grazing pressure by haptophytes and/or to NO3- and PO43- too rich conditions (Giraud et al., 2016). 431
Phytoplankton assemblage widely evolved in surrounding waters, from a predominance of pico-432
phytoplankton (Prochlorococcus) on D0 towards a higher abundance of micro-phytoplankton (diatoms) on D6. 433
In order to assess if the impact on the phytoplankton assemblage due to 10 % deep seawater addition (with a 434
shift towards the diatoms) was in the range of the natural variation observed in the surrounding surface waters, 435
10 % deep seawater microcosms phytoplankton assemblage was compared to the natural phytoplankton 436
assemblage. 437
Whereas microcosm controls showed a lower Prochlorococcus abundance (Fig. 7a) than surrounding 438
surface waters on D6 (p < 0.05), the 10 % microcosms additionally showed, higher fucoxanthin (diatoms) and 439
19’-butanoyloxyfucoxanthin (haptophytes) by about 142 % and 317 % (Fig. 6), respectively, as compared to 440
natural waters at D6. Furthermore, 10 % enrichments showed a fucoxanthin increase over the 6 days period by 441
3-times higher than in surrounding waters, whereas controls only showed an increase by 1.5-times higher than in 442
surrounding waters. Therefore, it can be concluded that the 10 % deep seawater enrichment induced higher 443
variations of the phytoplankton assemblage than those observed from D0 to D6 in surrounding surface waters. 444
17
VC were higher (p < 0.05) both in 2 % and 10 % enrichments on D0 as compared to controls, suggesting a 445
positive response of phytoplankton to the deep seawater addition. Conversely, there was no carbon-uptake 446
rate difference (p < 0.05) between controls and enriched waters (with 2 % and 10 % of deep seawater) at D6 447
with the 6 days incubated microcosms, suggesting that the observed community modifications did not change 448
the primary production. Indeed, the phytoplankton community was quite similar in surrounding surface waters 449
on D6 and in 6 days-incubated microcosm controls. Thus, only the initial phytoplankton assemblage and initial 450
primary production in surrounding surface waters would influence the response of the phytoplankton 451
community and its production. 452
At the BEL, after 6 days of incubation, deep seawater addition experiments clearly showed lower effects 453
on the phytoplankton community than at the DCM. Indeed, whereas significant differences (p < 0.05) between 454
10 % enrichments and controls were observed in diagnostic pigments concentrations at the DCM, pigments 455
concentrations were too low at the BEL to be quantified. It can be suggested that the lower population and 456
lower carbon uptake could be related to the lowest light availability. 457
Overall, the phytoplankton response was proportional to the amount of added deep seawater. If the 458
phytoplankton assemblage significantly varied over time in the environment, the 10 % deep seawater 459
enrichment showed larger variations (for diatoms and haptophytes) than those observed in the natural 460
environment. The DCM should be more impacted than the BEL by the deep seawater discharge even with a 461
large deep seawater input. On the other hand, the impact on the primary production largely depended on the 462
initial phytoplankton assemblage, which was quite variable over time. The modification of the phytoplankton 463
community to a deep seawater input could also be depending on the initial phytoplankton community. For that, 464
the microcosm experiments did not allow drawing a scenario over the long term of the potential modifications 465
of the primary production and the phytoplankton community associated to the deep seawater discharge by an 466
OTEC. 467
Finally, light microscopy analyses showed a large abundance of dinoflagellates at the DCM (between 9,240 468
and 20,400 cells.mL-1 on D6 and D4; Fig. 3 a) which could be mixotrophic or heterotrophic and thus probably 469
exert a grazing pressure on the phytoplankton, particularly on the pico-phytoplankton (Liu et al., 2002). 470
However, in this study, the zooplankton larger than 200 µm and its potential control on the phytoplankton 471
community were not considered and should be examined in future studies. 472
18
5. Conclusion 473
Two complementary approaches were applied to study the potential effects of the deep seawater 474
discharge of the planned OTEC plant on the phytoplankton community in oligotrophic waters off Martinique. 475
Because the distribution and the development of phytoplankton are directly linked to the surface 476
stratification, it is important to assess the thermal effect of deep seawater by an OTEC plant. Modelling of the 477
deep seawater discharge showed that the thermal structure of the top 150 m of the water column on large and 478
near-OTEC sections should be very slightly impacted for the lowest considered temperature differences 479
|ΔT| ≥ 0.3 °C. If World Bank Group prescriptions of not exceeding a higher temperature difference of 3 °C are 480
followed, the environmental perturbations potentially caused by the operation of the OTEC should be 481
considered negligible. The area where the 150 m-depth waters are impacted by the lowest considered 482
temperature differences |ΔT| ≥ 0.3 °C would not exceed 1 km2 in a worst-case scenario. 483
The phytoplankton community and its production could be impacted by a large deep seawater input. 484
Whereas pico-phytoplankton currently largely dominates the phytoplankton assemblage, a ratio of 10 % of 485
deep seawater in DCM waters could induce a shift toward the diatoms and micro-phytoplankton. The ratio of 2 486
% of deep seawater in DCM waters only showed significant higher Prochlorococcus abundance than controls, 487
but the assemblage and the primary production were not modified by this lower input. The stimulation of 488
Prochlorococcus could be due to one or some of the following causes: NO3- and/or PO43- supply, trace metal 489
supply, lowered pH (higher availability of dissolved inorganic carbon). Since the lower impact on the 490
phytoplankton assemblage was obtained at BEL, this depth can be recommended for the discharge the deep 491
seawater to exploit the OTEC plant. 492
Although significant, these results would have to be extended to larger temporal scale, and the 493
phytoplankton interactions with higher trophic levels (such as zooplankton) must be studied. 494
Because no environment standards on the deep seawater discharge effects are available yet, a rigorous 495
monitoring of the phytoplankton community, biogeochemical parameters distribution and of the water column 496
stratification must be established as soon as the OTEC is implemented and during its continuous functioning. 497
Acknowledgements 498
This work was supported by France Energies Marines and part of the IMPALA project. We would like to thank 499
the Captains and crew members of the “Pointe d’Enfer”, and the scientists in the laboratory at the University of 500
19
the French West Indies and Guiana at Martinique; Dominique Marie (UPMC, Roscoff, France) and Christophe 501
Lambert (LEMAR, France) for their help with the flow cytometry, and Anne Donval (LEMAR, France) for the 502
pigment analyses. 503
504
505
20
References 506
Agawin, N.S.R., Duarte, C.M., Agustí, S.: Nutrient and temperature control of the contribution of 507
picoplankton to phytoplankton biomass and production. Limnology and Oceanography, 45(8), 1891–1891, 508
2000. 509
Aminot, A., and Kérouel, R.: Dosage automatique des nutriments dans les eaux marines : méthodes en flux 510
continu. Ifremer Eds., Méthodes d’analyse en milieu marin, Quae, 2007. 511
Aure, J., Strand, O., Erga, S.R., Strohmeier, T.: Primary production enhancement by artificial upwelling in a 512
western Norwegian fjord, Marine Ecology Progress Series, 39–470 52, 2007. 513
Bakun, A.: Global climate change and intensification of coastal ocean upwelling, Science, 247(4939), 198–201, 514
1990. 515
Boyd, P. W., Jickells, T., Law, C. S., Blain, S., Boyle, E. A., Buesseler, K. O., et al.: Mesoscale iron enrichment 516
experiments 1993-2005: Synthesis and future directions, Science, 315(5812), 612–617, 2007. 517
Boyd, P.W., Rynearson, T.A., Armstrong, E.A., Fu, F., Hayashi, K., Hu, Z. et al.: Marine phytoplankton 518
temperature versus growth responses from polar to tropical waters–outcome of a scientific community-wide 519
study, PLoS One, 8(5), e63091, 2013. 520
Bruland, K. W., Rue, E. L., Smith, G. J.: Iron and macronutrients in California coastal upwelling regimes: 521
Implications for diatom blooms, Limnology and Oceanography, 46, 1661–1674, 2001. 522
Bruland, K.W.: Controls on trace metals in seawater, The Oceans and Marine Geochemistry, Treatise on 523
Geochemistry, 6, 23-47, 2003. 524
Brzezinski, M.A.: The Si:C:N ratio of marine diatoms. Interspecific variability and the effect of environmental 525
variables, Journal of Phycology, 21, 347–357, 1985. 526
Carr, M. E., and Kearns, E. J.: Production regimes in four Eastern Boundary Current systems, Deep Sea Research 527
Part II: Topical Studies in Oceanography, 50(22), 3199–3221, 2003. 528
Carton, J.A., and Giese, B.S.: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA), 529
Monthly Weather Review, 136(8), 2999–3017, 2008. 530
Casey, J. R., Lomas, M.W., Mandecki, J., Walker, D.E.: Prochlorococcus contributes to new production in the 531
Sargasso Sea deep chlorophyll maximum. Geophysical Research Letters, 34(10), 2007. 532
21
Chavez, F.P., Toggweiler, J.R.: Physical estimates of global new production: the upwelling contribution. In: 533
Summerhayes, C.P., Emeis, K.C., Angel, M.V., Smith, R.L., Zeitzschel, B. (Eds.), Upwelling in the Ocean: Modern 534
Processes and Ancient Records. Wiley, 313–320, 1995. 535
De Baar, H. J., Boyd, P. W., Coale, K. H., Landry, M. R., Tsuda, A., et al.: Synthesis of iron fertilization 536
experiments: from the Iron Age in the age of enlightenment, Journal of Geophysical Research: Oceans (1978–537
2012), 110(C9), 2005. 538
Duarte, C.M., Agusti, S., Agawin, N.S.R.: Response of a Mediterranean phytoplankton community to increased 539
nutrient inputs: a mesocosm experiment, Marine Ecology Progress Series, 195, 61–70, 2000. 540
Dugdale, R.C., and Wilkerson, F.P.: The use of 15N to measure nitrogen uptake in eutrophic oceans; 541
experimental considerations, Limnology and Oceanography, 31(4), 673–689, 1986. 542
Dulaquais, G., Boye, M., Rijkenberg, M.J.A., Carton, X.J.: Physical and remineralization processes govern the 543
cobalt distribution in the deep western Atlantic Ocean. Biogeosciences, 11(6), 1561–1580, 2014. 544
Dussart, B.M.: Les différentes catégories de plancton, Hydrobiologia, 26, 72–74, 1966. 545
Escaravage, V., Prins, T.C., Smaal, A.C., Peeters, J.C.H.: The response of phytoplankton communities to 546
phosphorus input reduction in mesocosm experiments, Journal of Experimental Marine Biology and Ecology, 547
198, 55–79, 1996. 548
Fernández, I., Raimbault, P., Garcia, N., Rimmelin, P., Caniaux, G.: An estimation of annual new production and 549
carbon fluxes in the northeast Atlantic Ocean during 2001, Journal of Geophysical Research: Oceans (1978–550
2012), 110(C7), C07S13, 2005. 551
Fielding, S.R.: Emiliania huxleyi specific growth rate dependence on temperature, Limnol. & Oceanogr, 58(2), 552
663–666, 2013. 553
Giraud, M. : Evaluation de l'impact potentiel d'un upwelling artificiel lié au fonctionnement d'une centrale à 554
énergie thermique des mers sur le phytoplancton, Doctorat de l'Université de Bretagne Occidentale, 150 p., 555
2016. 556
Giraud, M., Boye, M., Garçon, V., Donval, A., De La Broise, D.: Simulation of an artificial upwelling using 557
immersed in situ phytoplankton microcosms, Journal of Experimental Marine Biology and Ecology, 475, 80–88, 558
2016. 559
22
Goericke, R. and Welschmeyer, N.A.: The Marine Prochlorophyte Prochlorococcus Contributes Significantly to 560
Phytoplankton Biomass and Primary Production in the Sargasso Sea, Deep Sea Research Part I: Oceanographic 561
Research Papers, 40(11), 2283-2294, 1993. 562
Goericke, R., and Repeta, D.J.: The pigments of Prochlorococcus marinus: The presence of divinyl chlorophyll a 563
and b in a marine prochlorophyte. Limnology and Oceanography, 37, 425–433, 1992. 564
Gruber, N.: The marine nitrogen cycle: overview and challenges, Nitrogen in the marine environment, 1–50, 565
2008. 566
Handå, A., McClimans, T.A., Reitan, K.I., Knutsen, Ø., Tangen, K., Olsen, Y.: Artificial upwelling to stimulate 567
growth of non-toxic algae in a habitat for mussel farming, Aquaculture Research, 45, 1798–1809, 2014. 568
Harrison, W.G., Harris, L.R., Irwin, B.D.: The kinetics of nitrogen utilization in the oceanic mixed layer: Nitrate 569
and ammonium interactions at nanomolar concentrations, Limnology and Oceanography, 41(1), 16–32, 1996. 570
Hasle, G.R.: The inverted microscope method, In: Sournia, A. (Ed.), Phytoplankton Manual. UNESCO, Paris, 571
1988. 572
Hillebrand, H., Durselen, C.D., Kirchttel, D., Pollingher, U., Zohary, T.: Biovolume calculation for pelagic and 573
benthic microalgae, Journal of Phycology, 35, 403–424, 1999. 574
Hooker, S.B., Clementson, L., Thomas, C.S., Schlüter, L., Allerup, M., Ras, J., Claustre, H., et al.: NASA 575
Tech. Memo. 2012-217503, NASA Goddard Space Flight Center, Greenbelt, Maryland, 2012. 576
Hutchins, D.A., Hare, C.E., Weaver, R.S., Zhang, Y., Firme, G.F., DiTullio, G.R., Alm, M.B., Riseman, S.F., 577
Maucher, J.M., Geesey, M.E., Trick, C.G., Smith, G.J., Rue, E.L., Conn, J., Bruland, K.W.: Phytoplankton 578
iron limitation in the Humboldt current and Peru upwelling, Limnology and Oceanography, 47, 997–1011, 579
2002. 580
International Finance Corporation (IFC): World Bank Group, Environmental, Health, and Safety Guidelines for 581
Liquefied Natural Gas (LNG) Facilities, 2007. 582
Kagaya, S., Maeba, E., Inoue, Y., Kamichatani, W., et al.: A solid phase extraction using a chelate resin 583
immobilizing carboxymethylated pentaethylenehexamine for separation and preconcentration of trace elements 584
in water samples, Talanta, 79(2), 146–152, 2009. 585
Kress, N., Thingstad, T.F., Pitta, P., Psarra, S., Tanaka, T., Zohary, T., Groom, S., Herut, B., Mantoura, R.F.C., 586
Polychronaki, T., Rassoulzadegan, F., Spyres G.: Effect of P and N addition to oligotrophic Eastern 587
23
Mediterranean waters influenced by near-shore waters: a microcosm experiment, Deep Sea Research Part II: 588
Topical Studies in Oceanography, 52, 3054–3073, 2005. 589
Laws, E.A., Bidigare, R.R., Karl, D.M.: Enigmatic relationship between chlorophyll a concentrations and 590
photosynthetic rates at Station ALOHA, Heliyon, 2, e00156, 2016. 591
Liu, H., Suzuki, K., Saino, T.: Phytoplankton growth and microzooplankton grazing in the subarctic Pacific Ocean 592
and the Bering Sea during summer 1999, Deep Sea Research Part I: Oceanographic Research Papers, 49(2), 593
363–375, 2002. 594
Lundholm, N., Skov, J., Pocklington, R., Moestrup, Ø.: Studies on the marine planktonic diatom Pseudo-595
nitzschia. 2. Autecology of P. pseudodelicatissima based on isolates from Danish coastal waters, Phycologia, 596
36(5), 381–388, 1997. 597
Marie, D., Partensky, F., Vaulot, D., Brussaard, C.: Enumeration of phytoplankton, bacteria, and viruses in marine 598
samples, Current protocols in cytometry, 1–11, 1999. 599
Mawji, E., Schlitzer, R., et al.: The GEOTRACES intermediate data product 2014, Marine Chemistry, 177(1), 600
1-8, 2015, doi 10.1016/j.marchem.2015.04.005. ` 601
Milne, A., Landing, W., Bizimis, M., Morton, P.: Determination of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb in seawater 602
using high resolution magnetic sector inductively coupled mass spectrometry (HR-ICP-MS). Analytica Chimica 603
Acta, 665(2), 200–207, 2010. 604
National Oceanic and Atmospheric Administration (NOAA): Ocean thermal energy conversion final 605
environmental impact statement. Office of Ocean Minerals and Energy, Charleston, SC, 1981. 606
National Oceanic and Atmospheric Administration (NOAA): Ocean thermal energy conversion: Assessing 607
potential physical, chemical, and biological impacts and risks. University of New Hampshire, Durham, NH, 2010. 608
Nozaki, Y.: A fresh look at element distribution in the North Pacific Ocean, Eos Transaction, 78(21), 221, 1997. 609
Orr, J.C., Fabry, V.J., Aumont, O., Bopp, L., Doney, S.C., Feely, R.A., Gnanadesikan, A., Gruber, N., Ishida, A., Joos, F., Key, 610
R.M., Lindsay, K., Maier-Reimer, E., Matear, R., Monfray, P., Mouchet, A., Najjar, R.G., Plattner, G.K., Rodgers, K.B., Sabine, 611
C.L., Sarmiento, J.L., Schlitzer, R., Slater, R.D., Totterdell, I.J., Weirig, M.F., Yamanaka, Y., Yool, A.: Anthropogenic ocean 612
acidification over the twenty-first century and its impact on calcifying organisms, Nature, 437(7059), 681–686, 613
2005. 614
Partensky, F., Hess, W.R., Vaulot, D.: Prochlorococcus, a marine photosynthetic prokaryote of global 615
significance, Microbiology and Molecular Biology Reviews, 63 (1), 106–127, 1999. 616
24
Pauly, D., and Christensen, V.: Primary production required to sustain global fisheries, Nature, 374(6519), 255–617
257, 1995. 618
Platt, T., Rao, D. S., Irwin, B.: Photosynthesis of picoplankton in the oligotrophic ocean, Nature, 301, 702–704, 619
1983. 620
Rocheleau, G., Hamrick, J., Church, M.: Modeling the Physical and Biochemical Influence of Ocean Thermal 621
Energy Conversion Plant Discharges into their Adjacent Waters, Final Technical Report, U.S. Department of 622
Energy Award N° DE-EE0003638, Makai Ocean Engineering, Inc., Kailua, Hawaii, 2012. 623
Sarthou, G., Timmermans, K.R., Blain, S., Tréguer, P.: Growth physiology and fate of diatoms in the ocean: a 624
review, Journal of Sea Research, 53(1), 25–42, 2005. 625
Shchepetkin, A.F., and McWilliams, J.C.: Correction and commentary for “Ocean forecasting in terrain-following 626
coordinates: Formulation and skill assessment of the regional ocean modeling system” by Haidvogel et al., J. 627
Comp. Phys., 227, 3595–3624, Journal of Computational Physics, 228(24), 8985–9000, 2009. 628
Shchepetkin, A.F., and McWilliams, J.C.: The regional oceanic modeling system (ROMS): a split-explicit, free-629
surface, topography-following-coordinate oceanic model, Ocean Modelling, 9(4), 347–404, 2005. 630
Shelley, R. U., et al.: Controls on dissolved cobalt in surface waters of the Sargasso Sea: Comparisons with iron 631
and aluminum, Global Biogeochem. Cycles, 26(2), GB2020, doi:10.1029/2011GB004155, 2012. 632
Slawyk, G., Collos, Y., Auclair, J.C.: The use of the 13C and 15N isotopes for the simultaneous measurement of 633
carbon and nitrogen turnover rates in marine phytoplankton, Limnology and Oceanography, 22, 925–932, 1977. 634
Taguchi, S., Jones, D., Hirata, J.A., Laws, E.A.: Potential effect of ocean thermal energy conversion (OTEC) 635
mixed water on natural phytoplankton assemblages in Hawaiian waters. Bulletin of Plankton Society of 636
Japan, 34(2), 125–142, 1987. 637
Teira, E., Mouriño, B., Marañón, E., Pérez, V., Pazó, M.J., Serret P, de Armas, D., Escánez, J., Woodward, E.M.S., 638
Fernández, E.: Variability of chlorophyll and primary production in the Eastern North Atlantic Subtropical Gyre: 639
potential factors affecting phytoplankton activity. Deep-Sea Research I, 52, 569-288, 2005. 640
Thomas, C.R.: Identifying Marine Phytoplankton. Academic Press, Inc. San Diego, California, 1996. 641
Tovar-Sanchez, A., and Sañudo-Wilhelmy, S.A.: Influence of the Amazon River on dissolved and intra-cellular 642
metal concentrations in Trichodesmium colonies along the western boundary of the sub-tropical North Atlantic 643
Ocean, Biogeosciences, 8, 217–225, 2011. 644
25
Uitz, J., Claustre, H., Gentili, B., Stramski, D.: Phytoplankton class-specific primary production in the world's 645
oceans: seasonal and interannual variability from satellite observations, Global Biogeochemical Cycles, 24(3), 646
2010. 647
Van Oostende, N., Dunne, J. P., Fawcett, S. E., Ward, B. B.: Phytoplankton succession explains size-partitioning 648
of new production following upwelling-induced blooms, Journal of Marine Systems, 148, 14–25, 2015. 649
WoRMS Editorial Board: World Register of Marine Species. Available from http://www.marinespecies.org at VLIZ. 650
Accessed 2019-06-21. doi:10.14284/170), 2019. 651
652
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Tables 653
Table 1- Comparison of analyses of SAFe (Sampling and Analysis of iron) S and D2 reference samples 654
(http://www.geotraces.org/science/intercalibration) between ID-ICPMS values (this study) and the consensus 655
values. Our mean reagent blanks (based on all blank determinations) for dissolved Cd, Pb, Fe, Ni, Cu, Zn, Mn 656
and Co, and detection limits of ID-ICPMS estimated as three times the standard deviation of the mean reagent 657
blanks are also shown. 658
659
Cd (pM) Pb (pM) Fe (nM) Ni (nM) Cu (nM) Zn (nM) Mn (nM) Co (pM)
SAFe D2
This study 948.83 ± 65.95 28.86 ± 4.44 0.898 ± 0.098 8.60 ± 0.36 2.15 ± 0.16 7.29 ± 0.27 0.40 ± 0.05 40.12 ± 3.88
Consensus values 986.00 ± 23.00 27.70 ± 1.50 0.933 ± 0.023 8.63 ± 0.25 2.28 ± 0.15 7.43 ± 0.25 0.35 ± 0.05 45.70 ± 2.90
n= 20 20 18 19 22 13 23 23
SAFe S
This study 7.24 ± 1.57 48.42 ± 6.08 0.087 ± 0.025 2.56 ± 0.55 0.55 ± 0.06 0.07 ± 0.06 0.75 ± 0.05 2.85 ± 0.81
Consensus values 1.10 ± 0.30 48.00 ± 2.20 0.093 ± 0.008 2.28 ± 0.09 0.52 ± 0.05 0.07 ± 0.01 0.79 ± 0.06 4.80 ± 1.20
n= 25 27 15 25 30 10 27 28
Detection Limit 0.996 0.613 0.032 0.096 0.011 0.129 0.001 0.07
Blanks 0.716 1.809 0.061 0.040 0.019 0.129 0.003 0.32
660
661
27
Table 2- Area (km2) (average and root mean square) impacted in the top-150 m by a temperature difference 662
|ΔT| ≥ 0.3 °C on two vertical sections centered on the OTEC, considering eight depths of deep seawater 663
discharge (45, 80, 110, 140, 170, 250, 350, 500 m) (Giraud, 2016). 664
Annual mean June
Depth of deep
water
discharge
Large domain Near-OTEC
domain Large domain
Near-OTEC
domain
45 m 0.4 ± 0.4 0.0 ± 0.1 0.0 0.0
80 m 0.6 ± 0.7 0.1 ± 0.1 0.4 0.0
110 m 0.6 ± 0.5 0.0 ± 0.1 0.9 0.0
140 m 0.4 ± 0.5 0.1 ± 0.1 0.1 0.0
170 m 0.5 ± 0.8 0.0 ± 0.1 0.5 0.0
250 m 0.5 ± 0.7 0.1 ± 0.1 0.1 0.0
350 m 0.5 ± 0.5 0.1 ± 0.1 0.0 0.0
500 m 0.5 ± 0.5 0.1 ± 0.1 0.3 0.0
665
Table 3- Nitrate, silicate, phosphate and nitrite concentrations on June 16th 2014 (D4) at the deep chlorophyll 666
maximum (DCM), at the bottom of the euphotic layer (BEL), and at the deep seawater pumping depth. 667
Concentrations were measured at the OTEC site (0 % addition of deep waters) and calculated for 2 % and 10 % 668
deep seawater additions. 669
Depth
(m)
Deep
seawater
ratio
[NO3-]
(µM)
[Si(OH)4]
(µM)
[PO43-]
(µM)
[NO2-]
(µM)
DCM
0 % < 0.02 2.39 < 0.02 0.02
2 % 0.54 2.88 0.04 0.02
10 % 2.71 4.82 0.19 0.02
BEL
0 % < 0.02 1.46 < 0.02 0.32
2 % 0.54 1.96 0.04 0.32
10 % 2.71 3.98 0.19 0.29
1100 100 % 27.11 26.69 1.87 <0.02
670
28
Table 4- Concentrations of dissolved trace metals (in nM): Mn, Fe, Cd, Zn, Co, Ni, Cu, Pb measured on June 671
16th 2014 (D4) at the OTEC site at the DCM, BEL and 1100 m (0 % addition of deep waters), and their calculated 672
concentrations in the mixtures with 2 % and 10 % addition of deep water. 673
Depth
(m)
Deep
seawater
ratio
Mn (nM) Fe (nM) Cd (nM) Zn (nM) Co (nM) Ni (nM) Cu (nM) Pb (nM)
DCM
0 % 2.97 ± 0.17 1.08 ± 0.03 0.03 ± 0.01 1.54 ± 0.04 0.05 ± 0.00 2.22 ± 0.10 1.70 ± 0.18 0.03 ± 0.00
2 % 2.92 1.08 0.04 1.56 0.05 2.29 1.70 0.03
10 % 2.71 1.09 0.07 1.63 0.05 2.60 1.71 0.03
BEL
0 % 1.65 ± 0.04 0.68 ± 0.03 0.03 ± 0.00 0.65 ± 0.03 0.03 ± 0.00 2.26 ± 0.17 1.14 ± 0.10 0.03 ± 0.00
2 % 1.63 0.69 0.04 0.68 0.03 2.34 1.15 0.03
10 % 1.52 0.73 0.08 0.82 0.03 2.64 1.21 0.03
1100 100 % 0.34 ± 0.02 1.22 ± 0.05 0.45 ± 0.01 2.39 ± 0.07 0.06 ± 0.00 6.00 ± 0.13 1.80 ± 0.08 0.02 ± 0.00
674
Table 5- Definition of the diagnostic pigments used as phytoplankton biomarkers (taxonomic significance) and 675
associated phytoplankton size class (Uitz et al., 2010). 676
677
Diagnostic Pigments Abbreviations Taxonomic Significance Phytoplankton Size Class
Fucoxanthin Fuco Diatoms microplankton
Peridinin Perid Dinoflagellates microplankton
19'-hexanoyloxyfucoxanthin Hex-fuco Haptophytes nanoplankton
19'-butanoyloxyfucoxanthin But-fuco Pelagophytes and Haptophytes nanoplankton
Alloxanthin Allo Cryptophytes nanoplankton
chlorophyll b + divinyl
chlorophyll b TChlb Cyanobacteria, Prochlorophytes picoplankton
Zeaxanthin Zea Chlorophytes, Prochlorophytes picoplankton
678
679
680
29
Figure captions 681
Figure 1- Bathymetry of the parent and child (grey rectangle) domains interpolated from the GINA data base 682
with a zoom on the near domain (black rectangle); the oblique white and black lines represent the large and 683
small sections, respectively, used for numerical simulations. 684
685
Figure 2- Pigment concentrations (from HPLC analysis) at the OTEC site at the DCM (a) and at the BEL (b), on 686
June 12th (D0), 16th (D4), 18th (D6) 2014 (bars represent the standard deviation). 687
688
Figure 3- Abundance and biovolume of micro- and part of nano-phytoplankton at the OTEC site on June 12th 689
(D0), 16th (D4), 18th (D6) 2014, at the DCM (a and c, respectively) and at the BEL (b and d, respectively) (bars 690
represent the standard deviation). 691
692
Figure 4- Abundance of pico-phytoplankton at the DCM (a) and at the BEL (b), on June 12th (D0), 16th (D4), 18th 693
(D6) 2014 (bars represent the standard deviation). 694
695
Figure 5- Specific carbon uptake rate (µmol.(µg Chl a)-1.h-1) at the DCM (a) and BEL (b) depths, on June 12th 696
(D0), and 18th (D6), and in 6 days incubated microcosms (D6), for the three mixing conditions (0 %, 2 % and 10 697
% of deep seawater additions) (for surrounding waters bars represent the standard deviation for 2 replicates). 698
699
Figure 6- Diagnostic pigment concentrations in surrounding surface waters on D0 and D6, and in controls and 700
deep water-enriched (2 % and 10 %) microcosms after 6 days of incubation at the DCM (bars represent the 701
standard deviation). Similar letters (a, b or c) attributed to 2 or more treatments indicate no significant 702
differences (p < 0.05) between these treatments. 703
704
Figure 7- Abundance of picophytoplankton in surrounding surface waters on days 0 and 6, and in controls and 705
deep water-enriched (2 % and 10 %) microcosms after 6 days of incubation at 45 m depth (a) and 80 m depth 706
(b) (bars represent the standard deviation). Similar letters (a, b or c) attributed to 2 or more treatments indicate 707
no significant differences (p < 0.05) between these treatments. 708
30
Figure 1 709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
31
Figure 2 726
727
728
729
730
731
32
Figure 3 732
733
734
735
736
737
738
739
33
Figure 4 740
741
742
743
744
Figure 5 745
746
747
748
34
Figure 6 749
750
751
752
753
Figure 7 754
755
756
757
Figure 8: Diagnostic pigment concentrations in surrounding surface waters on days 0 and 6, and in controls and deep water-enriched (2% and 10%) microcosms after 6 days of incubation at the DCM (bars represent the standard deviation). Similar letters (a, b or c) attributed to 2 or more treatments indicate no significant
differences (p-value < 0.05) between these treatments.
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